install.packages("gapminder")
library(gapminder)

data("gapminder")
dim(gapminder)
summary(gapminder)
str(gapminder)

install.packages("dplyr")
library(dplyr)

gapminder %>%
  filter(country == 'Taiwan' |
         country == 'South Africa') %>%
  group_by(country) %>%
  summarise(avg_lifeExp = mean(lifeExp))

df_ttest <- gapminder %>%
  filter(country == 'Taiwan' |
        country == 'South Africa')
t.test(data = df_ttest, lifeExp ~ country)

install.packages("ggplot2")
library(ggplot2)

gg1 <- gapminder %>%
  filter(gdpPercap < 50000) %>% 
  ggplot(aes(x = gdpPercap, y = lifeExp)) +
  geom_point()

gg1

gg2 <- gapminder %>%
  filter(gdpPercap < 50000) %>% 
  ggplot(aes(x = gdpPercap, y = lifeExp, col = continent)) +
  geom_point(alpha = 0.3)

gg2

gg3 <- gapminder %>%
  filter(gdpPercap < 50000) %>% 
  ggplot(aes(x = gdpPercap, y = lifeExp, col = continent)) +
  geom_point(alpha = 0.3) +
  geom_smooth()

gg3

gg4 <- gapminder %>%
  filter(gdpPercap < 50000) %>% 
  ggplot(aes(x = gdpPercap, y = lifeExp, col = continent)) +
  geom_point(alpha = 0.3) +
  geom_smooth(method = "lm") +
  facet_wrap(~continent)

gg4

lucky_number <- 24
lucky_number

lucky_numbers <- c(24, 34)
lucky_numbers

?q
help(q)

# 利用 c() 函數 --------------------------
lucky_numbers <- c(24, 34) # 將 24 與 34 多個值指派給 lucky_numbers 物件
lucky_numbers              # 印出 lucky_numbers

class(24)

class("Luke Skywalker")

class(TRUE) # class(FALSE)

2 + 1
2 - 1
2 * 2
4 / 2
2**3
12 %% 8
17 %/% 8

height <- 172
weight <- 65
bmi <- ___ / (___)**2
bmi

luke <- "Luke Skywalker"
luke <- 'Luke Skywalker'

num_vector <- c(1, 2, 3, 4, 5)
num_vector > 2

num_vector[num_vector > 2]

if (條件一) {

    # 程式一

} else if (條件二) {

    # 程式二

} else {

    # 程式三

}

function_name <- function(input_1, input_2, params_1, params_2, ...) {
  # 一些描述
  return() #把輸出回傳
}

# 宣告函數
squared <- function(x) {
  return(x^2)
}

# 呼叫函數
squared(5)

# 宣告函數
abs_fun <- function(x) {
  if (x < 0) {
    return(-x)
  } else {
    return(x)
  }
}

# 呼叫函數
abs_fun(-5)

abs_fun(10)

get_bmi(172, 65)
## [1] 21.97134

name <- c("蒙其D魯夫", "羅羅亞索隆", "娜美", "賓什莫克香吉士")
is_female <- c(FALSE, FALSE, TRUE, FALSE)
age <- c(19, 21, 20, 21)
one_piece_df <- data.frame(name, is_female, age, stringsAsFactors = FALSE)
class(one_piece_df)
View(one_piece_df)

char_vector <- c("I", "Love", "R")
my_vector <- 1:8
name <- c("蒙其D魯夫", "羅羅亞索隆", "娜美", "賓什莫克香吉士")
is_female <- c(FALSE, FALSE, TRUE, FALSE)
age <- c(19, 21, 20, 21)
one_piece_df <- data.frame(name, is_female, age, stringsAsFactors = FALSE)
my_list <- list(char_vector, my_vector, one_piece_df)

get_bmi(172, 65)
## $bmi
## [1] 21.97134
## $label
## [1] "Normal"

# for 迴圈
for (i in month.name) {
  print(i)
}

# while 迴圈
i <- 1
while (i < 13) {
  print(month.name[i])
  i <- i + 1
}

get_length(c(1, 2, 3))
## [1] 3

get_sum(c(1, 2, 3))
## [1] 6

get_divisors(87)
## [1] 1 3 29 87

is_prime(87)
## [1] FALSE

count_primes(3, 10)
## [1] 3

fib_generator(0, 1, fib_len = 5)
## [1] 0 1 1 2 3

csv_file_path <- "Your csv file path"
df <- read.csv(csv_file_path)

txt_file_path <- "Your text file path"
df <- read.table(txt_file_path, sep = "Text file separator", header = TRUE)

install.packages("readxl")
library(readxl)

xlsx_file_path <- "Your excel file path"
df <- read_excel(xlsx_file_path)

install.packages("jsonlite")
library(jsonlite)

json_file_path <- "Your json file path"
data_list <- fromJSON(json_file_path)

install.packages("rvest")
library(rvest)

library(rvest)

html_doc <- "http://www.imdb.com/title/tt3783958/" %>%
  read_html()

elem <- html_doc %>%
  html_nodes(css = "strong span")
  # html_nodes(xpath = "//strong/span")

rating <- elem %>%
  html_text() %>%
  as.numeric()